Spiking time-dependent plasticity leads to efficient coding and predictions (Aceituno, MPI Leipzig)

Mai 28
28-05-2020 09:00 Uhr bis 09:45 Uhr
Online (contact marius.yamakou@fau to get the data for the VC)

Spiking time-dependent plasticity leads to efficient coding and predictions

Pau Aceituno, Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany

Latency reduction of postsynaptic spikes is a well-known effect of Spiking Time-Dependent Plasticity. We expand this notion for long postsynaptic spike trains, illustrating how it can be generalized to include inhibitory spike trains and some constraints on connectivity and neural activity. On the functional side, we show that a fixed presynaptic train induces early spike synchronization as well as a reduction in the number of postsynaptic spikes, thus improving neural codes. Finally, we show how this leads to predictions.

https://en.www.math.fau.de/applied-analysis

Friedrich-Alexander-Universität Erlangen-Nürnberg